Evidence map›Paper›PMID 39603580›Full record

ArticleThe American journal of cardiology2025

Abbreviated Duke Activity Status Index for Risk Stratification in Heart Failure.

Silvio Nunes Augusto, Yuping Wu, Thanat Chaikijurajai, Stanley L Hazen, W H Wilson Tang

Registry-linked trialAbstract read
In one paragraph

Article in The American journal of cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01685840 (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure.), which is not on this map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01685840 naterminatednot on this map

Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure.

TypeinterventionalSponsorDuke UniversityRan2012 to 2016Enrolled894ConditionsHeart FailureArmsUsual Care, Biomarker-guided care NT-proBNP
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Silvio Nunes AugustoCardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio.
Yuping WuCardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio; Cleveland State University, Cleveland, Ohio.
Thanat ChaikijurajaiDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
Stanley L HazenCardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio; Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio.
W H Wilson TangCardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio; Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio. Electronic address: tangw@ccf.org.

Funding

International Consortium for Multimodality Phenotyping in Adults with Non-compactionR01HL146754 · NHLBI · STANFORD UNIVERSITY · PI NIEMAN, KOEN, TANG, WAI HONG WILSON · 2020 to 2023
$3.0M
NHLBI NIH HHS R01 HL146754
6 · The paper itself

Abstract

The Duke activity status index (DASI), a self-administered 12-item questionnaire has been used to estimate functional capacity and recently demonstrated prognostic information. We aimed to develop an abbreviated version for clinical applications. Leveraging the Cleveland Clinic GeneBank Study, we developed an abbreviated DASI questionnaire (aDASI) with the machine learning XGBoost algorithm, with the goal of maintaining the accuracy and reliability of the original DASI. We validated the prognostic value of aDASI in a subset of patients with heart failure from GeneBank and an independent data set from the GUIDE-IT (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure; ClinicalTrials.gov NCT01685840) trial. The results confirmed the congruence and accuracy between the original and the abbreviated scores while reducing the number of questions (R = 0.97, p <0.001). The original DASI score and the aDASI exhibited a strong correlation in the GeneBank and predictive value for all-cause mortality at different time points in the GUIDE-IT cohort. In conclusion, the abbreviated DASI tracks with original DASI assessment and performs comparably to the original DASI questionnaire in predicting all-cause mortality.

Indexed as

Heart FailureAgedAlgorithmsFemaleHumansMachine LearningMaleMiddle AgedMulticenter Studies as TopicPrognosisRandomized Controlled Trials as TopicReproducibility of ResultsRisk AssessmentSurveys and QuestionnairesSurvival RateDuke activity status indexfunctional capacityheart failureprognosis

Identifiers

PMID39603580
PMCPMC11761384

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.